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https://gitlab.kitware.com/vtk/vtk-m
synced 2024-09-08 13:23:51 +00:00
63050f68fc
The `MultiBlock` class has been renamed to `PartitionedDataSet`, and its API has been refactored to refer to "partitions", rather than "blocks". Additionally, the `AddBlocks` method has been changed to `AppendPartitions` to more accurately reflect the operation performed. The associated `AssignerMultiBlock` class has also been renamed to `AssignerPartitionedDataSet`. This change is motivated towards unifying VTK-m's data model with VTK. VTK has started to move away from `vtkMultiBlockDataSet`, which is a hierarchical tree of nested datasets, to `vtkPartitionedDataSet`, which is always a flat vector of datasets used to assist geometry distribution in multi-process environments. This simplifies traversal during processing and clarifies the intent of the container: The component datasets are partitions for distribution, not organizational groupings (e.g. materials). Ref #405
104 lines
3.9 KiB
C++
104 lines
3.9 KiB
C++
//============================================================================
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// Copyright (c) Kitware, Inc.
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// All rights reserved.
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// See LICENSE.txt for details.
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//
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// This software is distributed WITHOUT ANY WARRANTY; without even
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// the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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// PURPOSE. See the above copyright notice for more information.
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//============================================================================
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#include <iostream>
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#include <thread>
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#include <vtkm/cont/Initialize.h>
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#include <vtkm/cont/PartitionedDataSet.h>
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#include "IOGenerator.h"
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#include "MultiDeviceGradient.h"
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#include "TaskQueue.h"
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//This demo shows off using vtk-m in multiple threads in two different ways.
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//
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//At a high level we have 2 primary threads, an IO thread and a Worker thread
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//The IO thread will generate all data using the vtk-m serial device, and
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//will post this data to a worker queue as a vtk-m partitioned dataset.
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//The Worker thread will pull down these vtk-m data and run a
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//vtk-m filter on the partitions.
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//The vtk-m filter it runs will itself have a worker pool which it will
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//distribute work too. The number of workers is based on what device adapters
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//are enabled but uses the following logic:
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// - If TBB is enabled construct a single TBB worker
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// - If CUDA is enabled construct 4 workers for each GPU on the machine
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//
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//Unfortunately due to some thread unsafe logic in VTK-m it is currently not
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//possible to have CUDA and TBB workers at the same time. So the class will
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//choose CUDA over TBB when possible.
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//Once the thread unsafe logic is fixed a machine that has a single CPU
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//and single GPU we should expect that we will have 2 primary 'main loop'
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//threads, and 5 threads for heavy 'task' work.
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void partition_processing(TaskQueue<vtkm::cont::PartitionedDataSet>& queue);
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int main(int argc, char** argv)
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{
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auto opts =
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vtkm::cont::InitializeOptions::DefaultAnyDevice | vtkm::cont::InitializeOptions::Strict;
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vtkm::cont::Initialize(argc, argv, opts);
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//Step 1. Construct the two primary 'main loops'. The threads
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//share a queue object so we need to explicitly pass it
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//by reference (the std::ref call)
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TaskQueue<vtkm::cont::PartitionedDataSet> queue;
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std::thread io(io_generator, std::ref(queue), 6);
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std::thread worker(partition_processing, std::ref(queue));
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//Step N. Wait for the work to finish
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io.join();
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worker.join();
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return 0;
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}
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//=================================================================
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void partition_processing(TaskQueue<vtkm::cont::PartitionedDataSet>& queue)
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{
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//Step 1. Construct the gradient filter outside the work loop
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//so that we can reuse the thread pool it constructs
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MultiDeviceGradient gradient;
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gradient.SetComputePointGradient(true);
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while (queue.hasTasks())
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{
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//Step 2. grab the next partition skipping any that are empty
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//as empty ones can be returned when the queue is about
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//to say it has no work
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vtkm::cont::PartitionedDataSet pds = queue.pop();
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if (pds.GetNumberOfPartitions() == 0)
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{
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continue;
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}
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//Step 3. Get the first field name from the partition
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std::string fieldName = pds.GetPartition(0).GetField(0).GetName();
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//Step 4. Run a multi device gradient
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gradient.SetActiveField(fieldName);
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vtkm::cont::PartitionedDataSet result = gradient.Execute(pds);
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std::cout << "finished processing a partitioned dataset" << std::endl;
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//Step 5. Verify each partition has a "Gradients" field
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for (auto&& partition : result)
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{
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// std::cout << std::endl << std::endl << std::endl;
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// std::cout << "partition: " << std::endl;
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// partition.PrintSummary(std::cout);
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if (!partition.HasField("Gradients", vtkm::cont::Field::Association::POINTS))
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{
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std::cerr << "Gradient filter failed!" << std::endl;
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std::cerr << "Missing Gradient field on output partition." << std::endl;
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break;
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}
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}
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}
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std::cout << "partition_processing finished" << std::endl;
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}
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